{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                             FILM  RT_user_norm  Metacritic_user_nom  \\\n",
      "0  Avengers: Age of Ultron (2015)           4.3                 3.55   \n",
      "1               Cinderella (2015)           4.0                 3.75   \n",
      "2                  Ant-Man (2015)           4.5                 4.05   \n",
      "3          Do You Believe? (2015)           4.2                 2.35   \n",
      "4   Hot Tub Time Machine 2 (2015)           1.4                 1.70   \n",
      "\n",
      "   IMDB_norm  Fandango_Ratingvalue  \n",
      "0       3.90                   4.5  \n",
      "1       3.55                   4.5  \n",
      "2       3.90                   4.5  \n",
      "3       2.70                   4.5  \n",
      "4       2.55                   3.0  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "reviews = pd.read_csv('fandango_scores.csv')\n",
    "cols = ['FILM', 'RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue']\n",
    "norm_reviews = reviews[cols]\n",
    "print(norm_reviews[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.7     2\n",
      "2.8     2\n",
      "2.9     5\n",
      "3.0     4\n",
      "3.1     3\n",
      "3.2     5\n",
      "3.3     4\n",
      "3.4     9\n",
      "3.5     9\n",
      "3.6     8\n",
      "3.7     9\n",
      "3.8     5\n",
      "3.9    12\n",
      "4.0     7\n",
      "4.1    16\n",
      "4.2    12\n",
      "4.3    11\n",
      "4.4     7\n",
      "4.5     9\n",
      "4.6     4\n",
      "4.8     3\n",
      "Name: Fandango_Ratingvalue, dtype: int64\n",
      "2.00     1\n",
      "2.10     1\n",
      "2.15     1\n",
      "2.20     1\n",
      "2.30     2\n",
      "2.45     2\n",
      "2.50     1\n",
      "2.55     1\n",
      "2.60     2\n",
      "2.70     4\n",
      "2.75     5\n",
      "2.80     2\n",
      "2.85     1\n",
      "2.90     1\n",
      "2.95     3\n",
      "3.00     2\n",
      "3.05     4\n",
      "3.10     1\n",
      "3.15     9\n",
      "3.20     6\n",
      "3.25     4\n",
      "3.30     9\n",
      "3.35     7\n",
      "3.40     1\n",
      "3.45     7\n",
      "3.50     4\n",
      "3.55     7\n",
      "3.60    10\n",
      "3.65     5\n",
      "3.70     8\n",
      "3.75     6\n",
      "3.80     3\n",
      "3.85     4\n",
      "3.90     9\n",
      "3.95     2\n",
      "4.00     1\n",
      "4.05     1\n",
      "4.10     4\n",
      "4.15     1\n",
      "4.20     2\n",
      "4.30     1\n",
      "Name: IMDB_norm, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "\n",
    "fandango_distribution = norm_reviews['Fandango_Ratingvalue'].value_counts()\n",
    "fandango_distribution = fandango_distribution.sort_index()\n",
    "\n",
    "imdb_distribution = norm_reviews['IMDB_norm'].value_counts()\n",
    "imdb_distribution = imdb_distribution.sort_index()\n",
    "\n",
    "print(fandango_distribution)\n",
    "print(imdb_distribution)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9Ez/W4Pc5qKofyigY3Dv0sQCAjRviPgdvr6oXVtVPVtXPJ/lIkseSzJ7krQDAFjDEZYWL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\neVlrsJrU3QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x84ed3f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(norm_reviews['Fandango_Ratingvalue'])\n",
    "#ax.hist(norm_reviews['Fandango_Ratingvalue'],bins=20)\n",
    "#ax.hist(norm_reviews['Fandango_Ratingvalue'], range=(4, 5),bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DjIyM9KWulStX9qUeaUsyzKRtzPDwMPvuO8D69eumuynSVmOYSduYkZGRJsjO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\nSs+YSZLSM2aSpPSMmSQpPWMmSUrv/wGrVfijJ9s/VQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x84337d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(5,20))\n",
    "ax1 = fig.add_subplot(4,1,1)\n",
    "ax2 = fig.add_subplot(4,1,2)\n",
    "ax3 = fig.add_subplot(4,1,3)\n",
    "ax4 = fig.add_subplot(4,1,4)\n",
    "ax1.hist(norm_reviews['Fandango_Ratingvalue'], bins=20, range=(0, 5))\n",
    "ax1.set_title('Distribution of Fandango Ratings')\n",
    "ax1.set_ylim(0, 50)\n",
    "\n",
    "ax2.hist(norm_reviews['RT_user_norm'], 20, range=(0, 5))\n",
    "ax2.set_title('Distribution of Rotten Tomatoes Ratings')\n",
    "ax2.set_ylim(0, 50)\n",
    "\n",
    "ax3.hist(norm_reviews['Metacritic_user_nom'], 20, range=(0, 5))\n",
    "ax3.set_title('Distribution of Metacritic Ratings')\n",
    "ax3.set_ylim(0, 50)\n",
    "\n",
    "ax4.hist(norm_reviews['IMDB_norm'], 20, range=(0, 5))\n",
    "ax4.set_title('Distribution of IMDB Ratings')\n",
    "ax4.set_ylim(0, 50)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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88clWmDTmf5vkgSRPWLb8CUn+9wnW/2iSq5LcmeTohNsCgI1sU4aQf/RUK9bwJ++Vq6pP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\nMQeAzv0/yWA7M5fEkR4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x84ed470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(norm_reviews['RT_user_norm'])\n",
    "ax.set_xticklabels(['Rotten Tomatoes'])\n",
    "ax.set_ylim(0, 5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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m5mwLeahHRMTnqS5feg+z/35+ukQuaSFY5m2IiF9RzST1rdJZ1D0R8Wvg4Zn5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\nA/2rlnX/Um9bAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x73d75b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_cols = ['RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue']\n",
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(norm_reviews[num_cols].values)\n",
    "ax.set_xticklabels(num_cols, rotation=90)\n",
    "ax.set_ylim(0,5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
